What is the main purpose of data filtering?

The main purpose of data filtering is to find a certain type of data needed. In the big data environment, the amount of data accumulates rapidly. In order to analyze the value contained in massive data, it is very important to filter out valuable data. Data filtering plays a vital role in the entire data processing process.

# Data screening plays an important role in mathematical modeling. It is the first step in mathematical modeling. Only by getting good data can we ensure the authenticity and accuracy of the results. In actual problems, the amount of data we encounter is often huge.

In order to ensure that the method we use can be implemented with the support of original data, we must filter the data to simplify the solution. At the same time, we must ensure that the filtered data is representative so that the results obtained are more accurate and real. The ultimate purpose of data screening applied to the computer industry is to prepare for data mining.

Data filtering includes three parts: data extraction, data cleaning, and data loading.

Purpose

The purpose of data filtering is to improve the availability of previously collected and stored relevant data, which is more conducive to later data analysis.

The value of data lies in the information it can reflect. However, when collecting data, we did not fully consider its future use. We only collected as much data as possible.

Secondly, in order to obtain the information contained in the data at a deeper level, it may be necessary to bring together different data sources to extract the required data. However, this requires solving the data that may appear in different data sources. Problems such as different structures, different names or different representations of the same data.

It can be said that the main purpose of data screening is to find a certain type of data required; the ultimate purpose is to prepare for data mining.

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